Salesforce-AI-Specialist Exam Practice Test Instant Access

Question 1

Universal Containers (UC) wants to create a new Sales Email prompt template in Prompt Builder using the "Save As" function. However, UC notices that the new template produces different results compared to the standard Sales Email prompt due to missing hyperparameters.

What should UC do to ensure the new prompt template produces results comparable to the standard Sales Email prompts?

AUse Model Playground to create a model configuration with the specified parameters.

BManually add the hyperparameters to the new template.

CRevert to using the standard template without modifications.

Answer : B

When Universal Containers creates a new Sales Email prompt template using the 'Save As' function, missing hyperparameters can result in different outputs. To ensure the new prompt produces comparable results to the standard Sales Email prompt, the AI Specialist should manually add the necessary hyperparameters to the new template.

Hyperparameters like Temperature, Frequency Penalty, and Presence Penalty directly affect how the AI generates responses. Ensuring that these are consistent with the standard template will result in similar outputs.

Option A (Model Playground) is not necessary here, as it focuses on fine-tuning models, not adjusting templates directly.

Option C (Reverting to the standard template) does not solve the issue of customizing the prompt template.

For more information, refer to Prompt Builder documentation on configuring hyperparameters in custom templates.

Question 2

An AI Specialist needs to create a Sales Email with a custom prompt template. They need to ground on the following dat

Opportunity Products Events near the customer Tone and voice examples

How should the AI Specialist obtain related items?

ACall prompt initiated flow to fetch and ground the required data.

BCreate a flex template that takes the records in question as inputs.

CUtilize a standard email template and manually insert the required data fields.

Answer : A

To ground a sales email on Opportunity Products, Events near the customer, and Tone and voice examples, the AI Specialist should use a prompt-initiated flow. This flow can dynamically fetch the necessary data from related records in Salesforce and ground the generative AI output with contextually accurate information.

Option B (flex template) does not provide the ability to fetch dynamic data from Salesforce records automatically.

Option C (manual insertion) would not allow for the dynamic and automated grounding of data required for custom prompts.

Refer to Salesforce documentation on flows and grounding for more details on integrating data into custom prompt templates.

Question 3

Universal Containers (UC) has implemented Generative AI within Salesforce to enable summarization of a custom object called Guest. Users have reported mismatches in the generated information.

In refining its prompt design strategy, which key practices should UC prioritize?

AEnable prompt test mode, allocate different prompt variations to a subset of users for evaluation, and standardize the most effective model based on performance feedback.

BCreate concise, clear, and consistent prompt templates with effective grounding, contextual role-playing, clear instructions, and iterative feedback.

CSubmit a prompt review case to Salesforce and conduct thorough testing In the playground to refine outputs until they meet user expectations.

Answer : B

For Universal Containers (UC) to refine its Generative AI prompt design strategy and improve the accuracy of the generated summaries for the custom object Guest, the best practice is to focus on crafting concise, clear, and consistent prompt templates. This includes:

Effective grounding: Ensuring the prompt pulls data from the correct sources.

Contextual role-playing: Providing the AI with a clear understanding of its role in generating the summary.

Clear instructions: Giving unambiguous directions on what to include in the response.

Iterative feedback: Regularly testing and adjusting prompts based on user feedback.

Option B is correct because it follows industry best practices for refining prompt design.

Option A (prompt test mode) is useful but less relevant for refining prompt design itself.

Option C (prompt review case with Salesforce) would be more appropriate for technical issues or complex prompt errors, not general design refinement.

Salesforce Prompt Design Best Practices: https://help.salesforce.com/s/articleView?id=sf.prompt_design_best_practices.htm

Question 4

Universal Containers tests out a new Einstein Generative AI feature for its sales team to create personalized and contextualized emails for its customers. Sometimes, users find that the draft email contains placeholders for attributes that could have been derived from the recipient's contact record.

What is the most likely explanation for why the draft email shows these placeholders?

AThe user does not have Einstein Sales Emails permission assigned.

BThe user does not have permission to access the fields.

CThe user's locale language is not supported by Prompt Builder.

Answer : B

When using Einstein Generative AI to create personalized emails, if placeholders appear in the draft email where data from a recipient's Contact record should be, the most likely reason is that the user lacks permission to access the necessary fields. Salesforce's field-level security may prevent users from viewing or utilizing certain data fields, resulting in placeholders being shown instead of the actual values.

Option B is correct because missing field permissions will cause placeholders in email drafts.

Option A (missing Einstein Sales Emails permission) is unlikely, as this would prevent email generation altogether, not just placeholders.

Option C (locale language issues) would more likely affect language-specific issues, not field placeholders.

Salesforce Email Template and Permissions Documentation: https://help.salesforce.com/s/articleView?id=sf.email_templates_field_permissions.htm

Question 5

Universal Containers (UC) is experimenting with using public Generative AI models and is familiar with the language required to get the information it needs. However, it can be time consuming for both UC's sales and service reps to type in the prompt to get the information they need, and ensure prompt consistency.

Which Salesforce feature should a Salesforce AI Specialist recommend to address these concerns?

AEinstein Recommendation Builder

BEinstein Copilot Action: Query Records

CEinstein Prompt Builder and Prompt Templates

Answer : C

For Universal Containers (UC), to reduce the time and ensure prompt consistency when using public generative AI models, the recommended feature is Einstein Prompt Builder and Prompt Templates. This feature allows teams to create reusable and consistent prompts for generative AI tasks, ensuring that all users receive uniform responses without having to type in detailed prompts manually every time.

Einstein Prompt Builder simplifies the creation of prompts, and Prompt Templates standardize the inputs, saving time for sales and service reps.

Option A (Einstein Recommendation Builder) is more focused on recommendations, not prompt standardization.

Option B (Einstein Copilot Action: Query Records) is for querying records, not generating AI-driven prompts.

Salesforce Prompt Builder Overview: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_overview.htm

Question 6

Universal Containers wants to use an external large language model (LLM) in Prompt Builder.

What should an AI Specialist recommend?

AUse Apex to connect to an external LLM and ground the prompt.

BUse BYO-LLM functionality in Einstein Studio,

CUse Flow and External Services to bring data from an external LLM.

Answer : B

Bring Your Own Large Language Model (BYO-LLM) functionality in Einstein Studio allows organizations to integrate and use external large language models (LLMs) within the Salesforce ecosystem. Universal Containers can leverage this feature to connect and ground prompts with external LLMs, allowing for custom AI model use cases and seamless integration with Salesforce data.

Option B is the correct choice as Einstein Studio provides a built-in feature to work with external models.

Option A suggests using Apex, but BYO-LLM functionality offers a more streamlined solution.

Option C focuses on Flow and External Services, which is more about data integration and isn't ideal for working with LLMs.

Salesforce Einstein Studio BYO-LLM Documentation: https://help.salesforce.com/s/articleView?id=sf.einstein_studio_llm.htm

Question 7

The marketing team at Universal Containers is looking for a way personalize emails based on customer behavior, preferences, and purchase history.

Why should the team use Einstein Copilot as the solution?

ATo generate relevant content when engaging with each customer

BTo analyze past campaign performance

CTo send automated emails to all customers

Answer : A

Einstein Copilot is designed to assist in generating personalized, AI-driven content based on customer data such as behavior, preferences, and purchase history. For the marketing team at Universal Containers, this is the perfect solution to create dynamic and relevant email content. By leveraging Einstein Copilot, they can ensure that each customer receives tailored communications, improving engagement and conversion rates.

Option A is correct as Einstein Copilot helps generate real-time, personalized content based on comprehensive data about the customer.

Option B refers more to Einstein Analytics or Marketing Cloud Intelligence, and Option C deals with automation, which isn't the primary focus of Einstein Copilot.

Salesforce Einstein Copilot Overview: https://help.salesforce.com/s/articleView?id=einstein_copilot_overview.htm

Salesforce Certified AI Specialist Exam Practice Test